Determination of the integrity of RNA

ABSTRACT

Methods, systems, and apparatus make a determination of a level of integrity of a sample of biomolecules. For example, the determination of the integrity of RNA in a sample may be done in a fast and reproducible manner, such that the user can be assured of accuracy of a test (e.g. quantitative polymerase chain reaction qPCR) on the sample and compare results of different samples. The determination of integrity of an RNA sample is performed by comparing a size profile to reference size profiles (degradation standards) obtained from degradation over different lengths of times. As the reference scale of the level of integrity is derived from the actual degradation that occurs in a sample, high accuracy, reproducibility, and efficiency is provided.

CROSS-REFERENCES TO RELATED APPLICATIONS

The present application claims priority from and is a non-provisionalapplication of U.S. Provisional Application No. 61/093,060, entitled“RNA Quality Factor” filed Aug. 29, 2008, the entire contents of whichare herein incorporated by reference for all purposes.

BACKGROUND

This invention generally relates to electrophoresis systems, and moreparticularly to using an electrophoresis system to determine anintegrity of the biomolecules in a sample.

Gene expression analysis is essential to an understanding of molecularprocesses involved in health and disease. The ability to accuratelyquantitate steady-state levels of RNA is critical for studying molecularmechanisms of gene expression regulation. RNA quantitation techniques(such as northern blots, DNA microarrays, and real-time quantitativePCR) rely on the use of not only pure, but also intact RNA (i.e. RNA ofhigh integrity). High-throughput gene expression analysis requiresrapid, reliable, and standardized evaluation of RNA integrity. Yet, themethods to accurately and objectively evaluate the integrity of RNAmolecules, prior to embarking on time-consuming, labor intensive, andcostly projects, are limited.

Spectrophotometric methods to evaluate RNA concentrations and purity arewell established and widely used. Absorbance at 260 nm (A260) gives anaccurate measure of RNA concentration, and the ratio A260/A280 is anaccepted indicator of the purity of an RNA preparation with respect toprotein or phenol contaminations. However, these methods by themselvesmay give misleading results because they do not give any information onDNA contamination, the degradation state, or integrity of the sample.While RNA concentration and quality are important parameters forsuccessful downstream applications, RNA integrity is of utmostimportance when applications involve RNA quantitation for geneexpression studies such as quantitative real-time RT-PCR and cDNAmicroarrays. Using partially degraded RNA from various states ofdegradation will lead to varying and incorrect quantitation results,both in microarray experiments and real-time PCR experiments.

The traditional method for assessing the integrity of an RNA sample isby visual inspection after electrophoresis on a formaldehyde agarose gelin the presence of a fluorescent dye (or other luminescent agent), suchas ethidium bromide. Observation of two sharp bands, one each for thelarge and small subunit ribosomal RNAs (rRNAs), with the intensity ofthe larger band being about twice that of the smaller band, isindicative of intact RNA. While this method is relatively quick andinexpensive, interpretation of the data requires a fair amount ofexperience, and is still prone to inconsistencies.

Another limitation of this technique using a formaldehyde agarose gel isa requirement of on the order of 200 nanograms (ng) of RNA to make anaccurate assessment of its integrity. However, when RNAs are extractedfrom tissues (such as biopsies) that are available in very limitedquantities, agarose gel analysis may not be possible.

A major improvement in RNA analysis occurred with the introduction ofmicrofluidics-based electrophoresis systems that require as little as100 pg of RNA to produce an electropherogram displaying two distinctivepeaks of rRNAs. The digital data composing the electropherogram can beused for a series of computer-based analyses. For example, RNA integritycan be evaluated and quantitated automatically by comparing the area ofthe peaks corresponding to the rRNAs. In theory, a 28S/18S rRNA ratioclose to 2 should be indicative of intact RNA. However, in reality, therRNA ratio may not be very reliable, e.g., because the peak areameasurements are dependent on the chosen start and end points of thepeaks.

Because of the limited utility of and reproducibility of rRNA ratios toassess RNA integrity, an existing method (Schroeder et al. US2006/0246577) attempts to provide a standardized scale for determiningRNA integrity. This method obtains a very large number ofelectropherograms and has trained experts assign a RNA integrity number(RIN). A neural network then determines the features (8 total) of anelectropherogram that correspond to certain RIN values. This method cantake quite a long time to prepare, e.g., due to the very large number ofelectropherograms required, the need for evaluation by trained experts,and the computational demands of the neural network. Additionally, thismethod can provide inaccuracies (inconsistencies) for the researcher,e.g., due to variances in the expert-assigned numbers and varied samplesused.

Therefore, it is desirable to have improved methods for determining anintegrity of a sample of RNA or other biomolecules.

BRIEF SUMMARY

Embodiments of the invention make a determination of a level ofintegrity of a sample of biomolecules. For example, the determination ofthe integrity of RNA in a sample may be done in a fast and reproduciblemanner, such that the user can be assured of accuracy of a test (e.g.quantitative polymerase chain reaction qPCR) on the sample and compareresults of different samples. The determination of integrity of an RNAsample is performed by comparing a size profile to reference sizeprofiles (degradation standards). As the reference scale of the level ofintegrity is derived from the actual degradation that occurs in asample, embodiments provide high accuracy, reproducibility, andefficiency in creating the standards. In one aspect, embodiments providea high-throughput method of determining RNA degradation, which may beimplemented in data analysis by a computer system.

According to one exemplary embodiment, a method of determining a levelof integrity of a sample of biomolecules is provided. A first sizeprofile of the sample of biomolecules is received, where the sizeprofile provides a measure of a distribution of values of at least onedimension of the biomolecules in the sample. A computing device comparesthe first size profile to a plurality of reference size profiles. Eachreference size profile is measured at a different time of degradation ofa reference sample of biomolecules, and each reference size profilecorrelates to a different level of integrity. Based on a similarity ofthe first size profile to one or more of the reference size profiles,the computing device determines the level of integrity of the sample ofbiomolecules.

According to other exemplary embodiments, computer readable medium andelectrophoresis systems that implement methods described herein are alsoprovided.

According to another exemplary embodiment, a method of manufacturing anelectrophoresis system is provided. At least one reference sample ofbiomolecules is received. A respective size profile of the referencesample of biomolecules is measured at each of a plurality of successivetimes of degradation of the reference sample. Each size profile ismapped to a level of integrity, where a size profile measured at a latertime of degradation maps to a lower level of integrity. The sizeprofiles may be stored in a computer readable medium of theelectrophoresis system along with the corresponding levels of integrityfor each size profile.

A better understanding of the nature and advantages of the presentinvention may be gained with reference to the following detaileddescription and the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A shows an electrophoresis system 100 according to embodiments ofthe present invention.

FIG. 1B shows an example of an electropherogram according to embodimentsof the present invention.

FIG. 2 is a flowchart illustrating a method 200 of manufacturing anelectrophoresis system that determines a level of integrity of a sampleaccording to embodiments of the present invention.

FIGS. 3A and 3B show different reference size profiles (marked asdifferent sample numbers) taken at different times of degradationaccording to embodiments of the present invention.

FIG. 4A shows a table 400 of a mapping of the reference size profiles410 (each one at a different time) to a level of integrity (RQI 450)according to embodiments of the present invention.

FIG. 4B shows a table 490 that provides which size profiles (degradationstandards) correspond to which color according to embodiments of thepresent invention.

FIG. 5 is a flowchart of a method 500 for determining a level ofintegrity of a sample of biomolecules according to embodiments of thepresent invention

FIG. 6 shows an electropherogram 600 with rRNA peaks and three regionswhose area ratios are used to define a size profile according toembodiments of the present invention.

FIG. 7 is a flowchart of a method 700 for determining a level ofintegrity of a sample of biomolecules using peak area ratios accordingto embodiments of the present invention.

FIG. 8 shows a block diagram of an exemplary computer apparatus usablewith system and methods according to embodiments of the presentinvention.

FIG. 9A is a table illustrating the reproducibility of RQI measurementsof intact and partially degraded RNA samples according to an embodimentof the present invention.

FIG. 9B is a table illustrating the lower limits of RNA concentrationsfor RNA detection and RQI determination according to an embodiment ofthe present invention.

FIG. 9C shows a table illustrating the impact of RNA degradation onreal-time qPCR CT according to an embodiment of the present invention.

FIGS. 10 A and 10B show the effect of RNA concentration on RQIdetermination according to an embodiment of the present invention.

FIG. 11 shows a comparison of electropherogram profiles and RQI valuesat different time points between natural RNase and heat-mediateddegradations according to an embodiment of the present invention.

FIG. 12 shows plots illustrating an assessment of RNA degradation byreal-time qPCR according to an embodiment of the present invention.

FIG. 13 is a plot illustrating a correlation between RQI and therelative amount of specific transcript RNA remaining according to anembodiment of the present invention.

DETAILED DESCRIPTION

Before a scientist performs tests on a sample of biomolecules, thescientist would like to know whether the biomolecules are intact (i.e.have high integrity). For example, if the scientist is studying acertain type of RNA, the scientist wants to know whether the RNA havebeen broken (low integrity) or have survived the travel from the tissueto the sample holder.

There are different characteristics of a sample to determine whether thesample is suitable for performing the test. The concentration measuresthe amount of biomolecules (e.g. relative to a solvent, such as water)in the sample. If the concentration is low, the test may not have enoughbiomolecules to obtain any measurement.

The quality of the biomolecules relates to the biomolecules themselves,such as contamination. For example, if the sample includes differenttypes of molecules (e.g. other molecules that are the same size as thebiomolecules of interest), the sample may not have good quality when thescientist is only interested in one or a few of the biomolecules. Thequality also includes the integrity of the biomolecules, which can beeven more prevalent than contamination.

As used herein, the term “integrity” is a measure (extent) of adegradation of the biomolecules of a sample, e.g., relative to astarting point (such as when the biomolecules are in tissue). Over time,the biomolecules (e.g. RNA) may cleave and become smaller particles.This degradation can causes errors as the test may not detect thebiomolecules because they have changed form (e.g. becoming smaller).Thus, in one aspect, a determination of integrity can test how similarthe biomolecules of the sample are relative to the biomolecules whenthey are in living tissue. As used herein, a “biomolecule” is anymolecule that has one state in a living organism and can degrade.

Since the size of a biomolecules is related to the integrity, the sizemay be used to measure the integrity. Electrophoreses techniques measurethe size particles, and thus are well suited for such integritymeasurements. Embodiments of the invention provide an accurate,efficient, and consistent way to measure the integrity of thebiomolecules of a sample.

FIG. 1A shows an electrophoresis system 100 according to embodiments ofthe present invention. As shown, the electrophoresis system 100 ismicrofluidics-based. However, other types of electrophoresis systems maybe used in other embodiments. These methods, which measure fluorescenceof a fluorophore bound to very small amounts of RNA, overcome many ofthe limitations of agarose gel electrophoresis. For example, as littleas 100 pg of RNA may be needed to produce an electropherogram displayingtwo distinctive peaks of rRNAs.

In operation, the biomolecules of sample 105 is provided into at leastone channel 110. The biomolecules of the sample 105 are driven throughthe channel 110 from left to right (motion depicted with an arrow) bythe voltage (V) 115. Note that the voltage may be positive or negative.As shown, the biomolecules have different sizes, which is depicted asdots of different sizes. For example, some of the biomolecules (e.g.RNA) may have a first length and others have a second length that islonger than the first length.

Biomolecules of different lengths will travel at different speeds.Smaller molecules will be accelerated to higher speeds since they areeasier to move with a same amount of force (i.e. the electrical forcewhich may be about the same for each distinct molecule). This differencein speed can be used to determine the size of the biomolecules.

As the biomolecules move through the channel 110, they reach a detectionregion 120. Since the biomolecules of different size move at differentspeeds, they will reach the detection region 120 at different times.Once a biomolecule reaches the detection region 120, the biomoleculereceives electromagnetic radiation 125 from a laser 130. Thebiomolecules have fluorescent dyes as a fluorescent intercalating agent.

When the radiation 125 is received by the biomolecules, the fluorescentagent is excited and emits its own electromagnetic radiation 135. Usingethidium bromide as the fluorescent dye can require on the order of 200ng of RNA to make an accurate assessment of its integrity. The amountneeded can be reduced by using alternative fluorescent dyes, e.g., to aslittle as 100 picograms (pg) of RNA.

A detector 140 receives the radiation 135 and measures the amount(strength) of the signal over time. The strength of the signal at aspecific instant in time will depend upon the number of biomoleculespresent in the detection region 120 during that time. In this manner,the number of particles with a specific size can be measured by lookingat a plot of the signal over time (an example of a size profile), whichis called an electropherogram in some embodiments. A size profileprovides a measure of a distribution of values of at least one dimension(e.g. length) of the biomolecules in the reference sample

FIG. 1B shows an exemplary electropherogram trace 170 as an example of asize profile of a sample of biomolecules. The Y axis shows a strength ofthe fluorescent signal in relative units (RU). The X axis is time asmeasured in seconds. The electropherogram trace 170 provides thedistribution of the size of the particles, with a higher RU valuecorresponding to more molecules of a particular size. Theelectropherogram trace 170 displays two distinctive peaks of rRNAs,which is normal for a sample having high integrity. Other sizesprofiles, e.g., ones that show differences spatially as opposed totemporally, may also be used in embodiments of the present invention.

In one embodiment, after the detector 140 reads a specific value at aninstant in time, the detector 140 can then send the one data point to acomputing system 150. In another embodiment, after the detector 140reads a whole trace, the detector 140 can then send the entire sizeprofile to the computing system 150, which analyzes the size profile todetermine a level of integrity. Accordingly, in one embodiment, theelectrophoresis system 100 combines quantitation and quality assessmentin a single apparatus. In one aspect, the level of integrity isdetermined by comparing the just measured size profile to reference sizeprofiles stored in a memory 155.

In one embodiment, the method of determining the level of integrity isbased on matching an RNA sample's size profile with the reference sizeprofiles (e.g. by comparing electropherograms). Since the RNAs degradeand therefore decrease in size, eventually disappearing, there is anaccumulation of fast-moving, low molecular weight components, while theamount of high molecular weight components is decreasing. In simpleterms, the components migrate towards the left end of theelectropherogram. It is therefore possible to establish a set of profilestandards—from intact to degraded—constituting a degradation referencescale from 10 (intact) to 1 (fully degraded).

A description of the creation of the reference size profiles (alsocalled degradation standards) follows.

FIG. 2 is a flowchart illustrating a method 200 of manufacturing anelectrophoresis system that determines a level of integrity of a sampleaccording to embodiments of the present invention. The electrophoresissystem (e.g. system 100) is capable of determining a level of integrityof a sample using reference size profiles (degradation standards) thatare stored in the electrophoresis system.

In step 210, one or more reference samples of biomolecules is received.A reference sample may be composed of a plurality of separate vials orother containers. The sample may also be subsequently split up into theseparate vials or other containers. However, each of the referencesamples have the same or similar initial integrity. In one aspect, thedegradation standards are generated from RNA of the same origin and thesame concentration.

In step 220, a first size profile of the reference sample ofbiomolecules is measured at a time zero. The time zero is taken as thestart of degradation, thus this first size profile is taken as having nodegradation. In some embodiments, the sample may actually have nodegradation relative to the tissue from which the sample was taken. Inother embodiments, the sample may have some or minimal degradation.

In step 230, a respective size profile of the reference sample ofbiomolecules is measured at each of a plurality of successive times ofdegradation of the reference sample. In one embodiment, when thereference sample is initially split into several containers, eachmeasurement may come from a different container.

The successive times may be widely varying, depending on the rate ofdegradation that is occurring. For example, the times may be periodic(e.g. every hour or ½ hour) or separated by different times (e.g.measured more often as the beginning relative to the end). Also, asdifferent biomolecules may degrade at different rates, different sets ofreference size profiles may be used depending on the biomolecules ofinterest. For example, in one embodiment, the times may be 0, 3, 5, 12,20, 25, 31, 40, 52, 90, 150, and 270 min.

In one embodiment, the respective size profile referred to relate to thereference size profiles that are used in later steps. For example, manysize profiles may be measured at varying times, but one some of thesereference size profiles are considered part of the plurality obtained(kept) in step 230.

In step 240, each size profile is mapped to a level of integrity,wherein a size profile measured at a later time of degradation maps to alower level of integrity. In one embodiment, the level of integrity ismeasured from 10 (intact, i.e. first size profile) to 1 (fullydegraded). In another embodiment, the mapping is performed to a colorscale. In yet other embodiments, a text based scale may be used.

In step 250, the size profiles associated with the corresponding levelof integrity are stored in a computer readable medium (e.g. memory 155)of the electrophoresis system. In one embodiment, the standards may bestored as the run files in a separate folder and deployed along with theapplication during the software installation process of theelectrophoresis system.

The size profile may be stored in any suitable form. In one embodiment,the size profile is a sequence of data points, each data point includingtime and the corresponding fluorescence value. In another embodiment,the size profile is a set of numerical values that describe the datapoints of the electropherogram, graph, stain, or other measure. Forexample, the size profile may be one or more ratios of different regionsof the electropherogram, as described in more detail later.

In one embodiment, the degradation standards were generated byincubating 12 human liver RNA samples at a concentration of 100 ng/ul(Experion RNA StdSens analysis kit) in TE (10 mM Tris-HCl pH 8.0, 1 mMEDTA) at 90° C. Electropherograms of the standards are shown on the FIG.3A.

FIGS. 3A and 3B show different reference size profiles (marked asdifferent sample numbers) taken at different times of degradationaccording to embodiments of the present invention. FIG. 3A showselectropherograms for 12 RNA degradation standards. FIG. 3B showsvirtual gel image of the 12 RNA degradation standards.

In FIG. 3B, L refers to the RNA ladder. A DNA ladder is a solution ofDNA molecules of different lengths used in electrophoresis as areference to estimate the size of unknown biomolecules.

In one aspect, the different standards show a regular progression ofdegradation over time. In other words, a significant (and sometimesequal) amount of degradation occurs between each sample. The timeschosen of the sample may vary, depending on the rate of degradation thatis occurring. The rate of degradation may vary based on an incubationtemperature or other external conditions.

As one can see, the peaks for the sample 1 (no degradation) migrate tothe left as time elapses. Such migration and change of peaks can be usedto identify a level of integrity of the biomolecules of a sample. Thelevel of integrity may be equal to or be composed of an RNA qualityindicator RQI when the biomolecules are RNA.

FIG. 4A shows a table 400 of a mapping of the reference size profiles410 (each one at a different time) to a level of integrity (RQI 450)according to embodiments of the present invention. The mapping may belinear or non-linear and have various forms. For example, if there were10 standards, a linear mapping would provide each successive sizeprofile having an RQI value 450 of one less than the previous sizeprofile.

The RNA area 420, RNA concentration, ratio 440 of peak 28S to peak 18S,and RQI classification 460 are also provided. The RNA area 420 is thetotal area under the curve in the electropherogram and may be used tonormalize certain features of the electropherogram traces, e.g., inorder to account for spurious shifts up and down in the traces. Forexample, an area of one region relative to another region (such as ratio440 of peak 28S to peak 18S, which is discussed later) may be normalized(e.g. divided) by the RNA total area 420.a

In the example shown, 12 the size profiles (degradation standards) 410are provided (e.g., the standards from FIG. 3A); however, any number ofstandards may be used. In one embodiment, the standards are linearlymapped to RQI 450 on the interval from 1 to 10, where 1 corresponds tothe most degraded standard (sample 12) and 10 corresponds to the mostintact standard (sample 1).

For a linear mapping of standard number to RQI 450, where the standardsare taken at shorter time intervals at first and then larger timeintervals later, the RQI value 450 decreases fast vs. time and thenbegins to level out at a low value (e.g. <2) for large times (e.g.greater than 1 hour). In one aspect, such a linear mapping when the timeperiods are not uniform may be used when the degradation betweendifferent standards corresponds to a same percentage of change indegradation. In such an example, more degradation (e.g., as measured bythe ratio 440) would occur initially (10 to 9) then from (7 to 6), but asimilar percentage may occur.

In other embodiments where the samples are taken at relatively equaltimes, the RQI value may decrease at the same speed over time. Anon-linear decrease (e.g. fast at first) in RQI 450 vs. time would bemore common at a higher temperature (e.g. 90° C.), whereas a more lineardecrease might occur at room temperature (27° C.). However, in eithercase, the standards may correspond to roughly equal amounts ofdegradation.

The degradation standards 410 or the RQI 450 may also mapped to a RQIclassification 460, which may be a simple color coded scheme to identifyif a sample is good or not. Text based classifying schemes may also beused. The RQI classification 460 may be defined by the user, and alsomay correspond to a level of integrity.

FIG. 4B shows a table 490 that provides which size profiles (degradationstandards) correspond to which color according to embodiments of thepresent invention. In one embodiment, relationships between the colorscale and the reference size profile number or a numerical level ofintegrity (e.g. RQI 450), which may be normalized, are defined in thesettings and can be changed by the user.

The RQI 450 (or equivalently RQI classification 460 as a result of amapping) can be used as a standardized measure of RNA integrity acrosssamples and experiments. It provides an objective and consistentcriterion to select samples that meet minimal integrity levels requiredfor specific downstream applications. The connection between RQI valueand the utility of a sample for a specific downstream application has tobe determined empirically by the user. Once this value is known, it canbe used to specify the color code used in a run summary page, e.g., on auser interface of the computing system 150.

In some embodiments, the level of integrity is provided as the RNAquality indicator (RQI). The RQI can be used to measure RNA integrity bycomparing the electropherogram of RNA samples to the series ofstandardized degraded RNA samples. As described above, a number between10 (intact RNA) and 1 (highly degraded RNA) can be returned for eacheukaryotic RNA sample run on an electrophoresis system.

FIG. 5 is a flowchart of a method 500 for determining a level ofintegrity of a sample of biomolecules according to embodiments of thepresent invention. The sample of biomolecules is the sample for which itis desired to determine the level of integrity. In one embodiment, ifthe sample is contaminated (e.g. has a low quality due to othermolecules), then the method 500 is aborted. In one aspect, the user canidentify the quality by visual inspection of an output of anelectrophoresis system.

In step 510, a first size profile of the sample of biomolecules isreceived. The size profile provides a measure of a distribution ofvalues of at least one dimension of the biomolecules in the sample. Thesize profile may be measured by a detector of an electrophoresis systemand sent to a separate computing system or one that is part of theelectrophoresis system.

In step 520, a computing device (e.g. computing system 150) compares thefirst size profile to a plurality of reference size profiles. In oneaspect, each reference size profile is measured at a different time ofdegradation of a reference sample of biomolecules. In another aspect,each reference size profile correlates to a different level ofintegrity. For example the reference size profiles resulting from method200 may be used, with the RQI of FIG. 4A being used to determine the RQIvalue of the sample.

In one embodiment, the first size profile may be compared to another setof reference size profiles as well. This may be done in order to providean average of levels of integrity from different reference samples.

In an embodiment, the ratios of peaks in a size profile may be used forthe comparison. In another embodiment, the comparison may take the formof identifying the size profile on a functional fit that approximatesthe reference size profiles. Thus, since the functional fit is definedby the reference size profiles, such an identification provides acomparison to the reference size profiles. In yet another embodiment,the comparison may be performed by computing an overlap value betweenthe two profiles, e.g., calculating an area of overlap of two normalizedelectrophoretic traces.

In step 530, the computing device determines the level of integrity ofthe sample of biomolecules, based on a similarity of the first sizeprofile to one or more of the reference size profiles. The exact methodfor determining the level of integrity can be varied. For example, thelevel of integrity of the reference size profile that is most similar tothe first size profile may be used as the level of integrity for thefirst size profile. The level of integrity of the first size profile mayalso be taken as an average of the levels of integrity of two or moresize profiles that are similar. For example, the first size profile maylie between two reference size profiles, and a weighted average of thelevels for those two reference size profiles may be used.

In one embodiment, an interpolation (e.g. weighted linear combination ofthe RQIs of each of the reference size profiles) may be used. The linearcoefficients may be considered as a measure of an overlap (or other typeof similarity) of the first size profile to the size profile of aparticular reference size profile.

In one aspect, method 500 maps measurements in an N-dimensional space(e.g. fluorescent signal values) into a simplified single dimensionalspace. As described herein, the simplified expression may be a number(RQI value), color, or other classification. In one embodiment, the RQIvalue is defined as: I_(S)=I_(i)α_(i), where I_(i) is a set of integritynumbers assigned to the standards, and where α_(i) is a measure ofsimilarity (e.g. overlap) of the first size profile to the ith referencesize profile.

The underlying physics of the RNA degradation and peculiarities of thesignal measurements makes it reasonable to assume that thedegradation-related characteristics can be presented as a ratio of thesignal values over different intervals. In one aspect, forsample-to-sample compatibility, the intervals should be selected in thevicinity of a distinctive mark related to the molecules of the samesize. In one embodiment, Ribsomal RNA (rRNA) peaks are used as thedistinctive marks. In this manner, a shifting in time of theelectropherogram can be accounted for.

FIG. 6 shows an electropherogram 600 with rRNA peaks and three regionswhose area ratios are used to define a size profile according toembodiments of the present invention. As with the electropherogram ofFIG. 1B, the Y axis is the fluorescence and the X axis is time insecond.

Region 1 relates to a pre-18S peak area, region 2 relates to the 18Speak area, and region 3 relates to the 28S peak area. The differentareas are calculated by determining the area under the curve 610 for thewidth of a particular region. The 28S:18S and 18S:pre-18S ratios, aswell as any RNA concentrations may be automatically calculated.

In an embodiment, the 18S peak region and the 28S peak region aredefined by the peaks within the respective regions. A user can identifya particular time window or part of the electropherogram in which tosearch for these peaks. The system software can find the peaks and thenlocate the regions around the peaks. The final widths may be the same asthe time window that the user entered to find the peaks, or the widthsmay be different. In one embodiment, the pre-18S width is the same asthe 18S width. In another embodiment, the start of the 18S region may bedetermined when the signal reaches a threshold value.

Accordingly, in one embodiment, an area ratio of the ribosomal fragments(e.g. the area ratios of region 3 to 2 and/or the area ratios of region1 to 2) may be used to define a size profile. For example, a sizeprofile may be defined by these two ratios. These one or more ratios maybe what is stored as a reference size profile. These area ratios areexamples of size features of a size profile. Other suitable sizefeatures, such as peak heights or time location for a peak may be used.

The 28S/18S ratio generally decreases during continued degradation, andthe pre-18S/18S ratio generally increases during continued degradation.Thus, each of the different standards will generally have a differentratio (i.e. there is a one to one mapping of the area ration to astandard and an RQI value). Accordingly, these ratios may be used todetermine a level of integrity (e.g. an RQI) of a sample.

FIG. 7 is a flowchart of a method 700 for determining a level ofintegrity of a sample of biomolecules using peak area ratios accordingto embodiments of the present invention. In one embodiment, method 700uses the pre-18S/18S ratio and the 28S/18S ratios to define a sizeprofile. In one aspect, method 700 can take 30 minutes from start of arun of the electrophoresis process on the sample to obtaining the levelof integrity.

In step 710, regions near a distinctive peak (or other marking) aredetermined. In one embodiment, three regions are the pre-18S (below the18S rRNA band), 18S, and 28S regions of an electropherogram, as shown inFIG. 5. The 28S and 18S ribosomal peaks are prominent components ofintact RNA, while pre-18S and 18S regions of the electropherogram areprominent components in assessing degraded RNA. In another embodiment,only one of the ratios is used.

In step 720, ratios of the areas of the regions are calculated. In oneembodiment, the pre-18S/18S ratio and the 28S/18S ratios are calculatedas defining the first size profile of the sample whose level ofintegrity is to be determined. Note that the inverse of the ratios mayalso be used. In another embodiment, the areas for each region arenormalized by the entire area under the curve.

In one embodiment, a user can directly redefine ribosomal fragmentson-screen (i.e. a display of the electropherogram trace). For example,the user can change a fragment start and/or end, thereby causing achange in a position of the region(s) and an area of the region(s). Asanother example, the user can adjust a width of a region. In anotherembodiment, the user can adjust peak finding parameters in the software,which can affect the position and area of a region.

In step 730, an individual RQI (integrity value) for each of the ratiosis determined for the sample by comparing to the corresponding ratios ofa plurality of reference ratios defining a set of reference sizeprofiles. In one embodiment, the pre-18S/18S ratio increases betweeneach reference size profile of a lower integrity, thus this ratio of thesample can be placed between the ratios of two reference size profiles.Thus, the closest standards can define the sample degradation index(i.e. level of integrity of the sample). In one aspect, the sampledegradation index may be calculated as a normalized linear interpolationbetween the two closest standards.

For example, the pre-18S/18S ratio of the first size profile may have avalue of 1.5, which lies between values of 1.3 (corresponding to RQI of8) and 1.7 (corresponding to RQI of 6) of the reference size profiles.Thus, the RQI for the pre-18S/18S ratio of the first size profile may betaken as 7, an equal weighted average of the values (1.3 and 1.7). Ifthe pre-18S/18S ratio was closer to 1.7, the weighted average wouldfavor 6, and the RQI would be less than 7. A similar procedure may bedone for a 28S/18S ratio that decreases for reference size profiles of alower integrity.

In another embodiment, the data points of the pre-18S/18S ratio vs. RQImay be fit to a functional form (e.g. using least squares,interpolation, or any other suitable fitting method). Thus, a specificvalue of the functional form will map a value of the pre-18S/18S ratioto an RQI value. The functional form may be stored in an electrophoresissystem as the reference size profiles. Note when the value of thepre-18S/18S ratio is determined from the functional form, the value fromthe reference size profiles are still being compared. The 28S/18S ratiomay be determined in the same manner.

A level of integrity for the sample is then determined from theindividual RQIs of the two ratios for the first size profile. Forexample, a weighted average may be taken. To determine, such a weightingthe following steps may be done.

In step 740, weightings for individual RQIs are determined based onindividual RQIs (or equivalently the ratios values when there is a 1-1mapping). In one embodiment, the weightings are determined based on therelation of the individual RQIs to each other. In another embodiment,the weightings are determined based on the relation of the individualRQIs to an absolute value.

In one embodiment, one of the ratios or equivalently the RQIcorresponding to the ratio is compared to a threshold value. Forexample, the 28S/18S ratio or equivalently the RQI of the 28S/18S ratiois compared to a threshold value. In one embodiment, the threshold ofthe RQI is 6. Depending on this comparison, different weights are used.The pre-18S/18S ratio may be compared to a threshold instead.

If the RQI of the 28S/18S ratio is greater than the threshold, then theRQI of the 28S/18S ratio has a greater weighting in the average. In oneembodiment, the 28S/18S ratio is weighted by a factor three over thepre-18S/18S ratio if the 28S/18S ratio is greater than the threshold. Inanother embodiment, the 28S/18S ratio and the pre-18S/18S ratio areweighted equally.

Accordingly, in one embodiment, differential weighting is used toevaluate components of the electropherogram, based on how the samplemaps to the reference standards. In cases where the RNA sample maps to amore degraded standard, more emphasis is placed on the pre-18S and 18Sregions of the electropherogram for generating the RQI value. In othercases where the RNA sample maps to a higher integrity standard, moreemphasis is placed on the 28S and 18S regions. The initial determinationmay be made from the individual RQIs for either of the ratios.

In step 750, level of integrity is calculated from individual RQIs usingthe determined weightings. For example, an average using the weightingmay be used.

In summary, embodiments provide methods and electrophoresis systems thatoffer a robust assessment of RNA integrity. In one embodiment, threeregions of an electrophoretic profile are compared to a series ofdegradation standards. As shown in the examples section, embodiments areshown to work well over a wide range of RNA concentrations (100 pg to5,000 ng), is very reproducible (% CV<3), and is applicable to a widerange of mammalian tissues. Also, the applicability has beendemonstrated in a report showing a strict correlation between RQI valuesand RNA quantitation results by real-time PCR.

Accordingly, embodiments can check for RNA degradation using automatedseparation, detection, and data analysis. Also, embodiments provide auseful tool to quantitatively assess integrity of RNA samples beforeembarking on labor-intensive and costly projects, and enable thestandardization of sample testing for microarray and quantitativereal-time PCR analyses. This process, paired with chip priming stationand proprietary software, provides improved data generation, storage,and reporting. Additionally, minimal sample requirements mean that auser won't waste a drop of previous samples.

FIG. 8 shows a block diagram of an exemplary computer apparatus usablewith system and methods according to embodiments of the presentinvention. For example, the computer apparatus is usable as or as partof the computing system 150 of FIG. 1A.

Any of the PLC or computer terminal may utilize any suitable number ofsubsystems. Examples of such subsystems or components are shown in FIG.8. The subsystems shown in FIG. 8 are interconnected via a system bus875. Additional subsystems such as a printer 874, keyboard 878, fixeddisk 879, monitor 876, which is coupled to display adapter 882, andothers are shown. Peripherals and input/output (I/O) devices, whichcouple to I/O controller 871, can be connected to the computer system byany number of means known in the art, such as serial port 877. Forexample, serial port 877 or external interface 881 can be used toconnect the computer apparatus to a wide area network such as theInternet, a mouse input device, or a scanner. The interconnection viasystem bus allows the central processor 873 to communicate with eachsubsystem and to control the execution of instructions from systemmemory 872 or the fixed disk 879, as well as the exchange of informationbetween subsystems. The system memory 872 and/or the fixed disk 879 mayembody a computer readable medium.

The specific details of the specific aspects of the present inventionmay be combined in any suitable manner without departing from the spiritand scope of embodiments of the invention. However, other embodiments ofthe invention may be directed to specific embodiments relating to eachindividual aspects, or specific combinations of these individualaspects.

It should be understood that the present invention as described abovecan be implemented in the form of control logic using hardware and/orusing computer software in a modular or integrated manner. Based on thedisclosure and teachings provided herein, a person of ordinary skill inthe art will know and appreciate other ways and/or methods to implementthe present invention using hardware and a combination of hardware andsoftware

Any of the software components or functions described in thisapplication, may be implemented as software code to be executed by aprocessor using any suitable computer language such as, for example, C#,Java, C++ or Perl using, for example, conventional or object-orientedtechniques. The software code may be stored as a series of instructions,or commands on a computer readable medium for storage and/ortransmission, suitable media include random access memory (RAM), a readonly memory (ROM), a magnetic medium such as a hard-drive or a floppydisk, or an optical medium such as a compact disk (CD) or DVD (digitalversatile disk), flash memory, and the like. The computer readablemedium may be any combination of such storage or transmission devices.

Such programs may also be encoded and transmitted using carrier signalsadapted for transmission via wired, optical, and/or wireless networksconforming to a variety of protocols, including the Internet. As such, acomputer readable medium according to an embodiment of the presentinvention may be created using a data signal encoded with such programs.Computer readable media encoded with the program code may be packagedwith a compatible device or provided separately from other devices(e.g., via Internet download). Any such computer readable medium mayreside on or within a single computer program product (e.g. a hard driveor an entire computer system), and may be present on or within differentcomputer program products within a system or network. A computer systemmay include a monitor, printer, or other suitable display for providingany of the results mentioned herein to a user.

The above description of exemplary embodiments of the invention has beenpresented for the purposes of illustration and description. It is notintended to be exhaustive or to limit the invention to the precise formdescribed, and many modifications and variations are possible in lightof the teaching above. The embodiments were chosen and described inorder to best explain the principles of the invention and its practicalapplications to thereby enable others skilled in the art to best utilizethe invention in various embodiments and with various modifications asare suited to the particular use contemplated.

A recitation of “a”, “an” or “the” is intended to mean “one or more”unless specifically indicated to the contrary.

EXAMPLES

The following examples are offered to illustrate, but not to limit theclaimed invention.

I. Reproducibility

Interchip reproducibility of RQI values was evaluated by analyzing amouse brain total RNA sample (Ambion) at 250 ng/jJl on six differentchips with 12 samples per chip (n=72). The RQI values returned rangedbetween 8.7 and 9.7 with a mean RQI value of 9.4 and a percentcoefficient of variation (% CV) of 3.5%. Reproducibility of RQImeasurements on a less intact sample of rat liver RNA run at twodifferent concentrations, 100 ng/jJl and 2 ng/jJl, showed a highreproducibility across 12 and 11 runs using the Experion RNA 8td8ens andHigh8ens analysis chips, respectively. All RQI values fell into a tightrange with a low standard deviation, as shown in Table 1 of FIG. 9A.Together, these data show that RQI values are very reproducible.

II. Effect of Concentration

The effect of RNA concentration on RQI precision was determined byanalyzing RNA samples with different levels of integrity. RNA sampleswere diluted to cover the entire dynamic range of the standard andhigh-sensitivity RNA chips. The qualitative detection range is 5-500ng/fJl and 100-5,000 pg/fJl for Experion RNA StdSens and HighSens chips,respectively, as shown in Table 2 of FIG. 9B.

FIGS. 10 A and 10B show the effect of RNA concentration on RQIdetermination according to an embodiment of the present invention. Todetermine the lower limit of RNA concentrations for RQI determinationusing the Experion RNA StdSens chip, four samples of RNA from mouse andrat liver with different levels of integrity (RQI values ranging between−3 and 9, FIGS. 10A, B) were used. Twelve serial dilutions (between1-100 ng/μl) were prepared from each sample and run in triplicate onthree StdSens analysis chips. The reported RQI values at eachconcentration, as measured by the Experion system (FIG. 10A), indicatethat a correct RQI value (within 1 unit of its expected value) isreturned for RNA concentrations above 10 ng/μl.

The lower limit of RNA concentrations for RQI determination with theHighSens analysis chip was determined using an intact mouse liver RNAsample. Twelve RNA concentrations ranging between 10-10,000 pg/μl wereanalyzed in triplicate using HighSens analysis chips, The results (FIG.10B) indicate that the RQI value is accurately reported (within 1 unitof its expected value) above 200 pg/μl with the Experion RNA HighSensanalysis chip.

These experiments showed that a reliable RQI value is reported at orbelow the actual lower limit of quantitative detection for RNA for bothExperion RNA chips (Table 2 of FIG. 9B). For samples whoseconcentrations fall below these thresholds, the Experion system cannotreliably report a valid RQI value and conveniently flags the sample byproviding the comment “RNA conc. too low”. This cutoff can be overriddenby the user by checking a box in the RQI settings, allowing display ofthe values in brackets.

III. Application to Different Tissue and Organism

Embodiments have established reference size profiles using human liverRNA samples for standards and are intended to be used on eukaryoticsamples. To test the applicability of the embodiments to different RNAsample types, a variety of different sample tissues and sources wereevaluated. These included a series of 20 human RNA samples fromdifferent tissues (FirstChoice human total RNA survey panel, Ambion).This study indicated that the RQI method can be used to assess integrityof RNA from a variety of human tissues and compared to measured RINvalues. Additionally, hundreds of RNA samples were extracted and RQIvalues measured for a variety of tissues and organisms, including mouseliver, heart, brain, skin, cartilage, and skeletal muscle; rat brain andliver; rabbit lung; human neural blastoma biopsy samples; humanendometrium biopsy samples; and HeLa, Jurkat, and HEPG2 cultured cells.All RQI values, independent of the methods used for RNA extraction (TRIreagent or membrane-based methods, such as Bio-Rad's Aurum total RNAfatty and fibrous tissue kit or Aurum total RNA mini kit), could beconfirmed by visual interpretation of the electropherograms.

Although embodiments of reference size profiles created in one tissueand organisms have been shown to be applicable in a variety of tissuesand organisms, different standards (reference size profiles) may be usedfor different tissues and for same tissue but different organism.

IV. Accuracy for RNase Degradation

The RQI algorithm was established using heat-degraded RNA as referencesamples. However, degradations that occur during the RNA extractionprocedure are generally caused by the action of endogenous or exogenousRNases. To assess the validity of the RQI algorithm on such samples, RQImeasurements of heat- and RNase-degraded RNA samples were compared.Endogenous RNase degradation was induced by incubating tissues (liver)at room temperature prior to RNA extraction. The two types ofdegradations yielded significantly different electrophoresis profiles asshown in FIG. 11.

FIG. 11 shows a comparison of electropherogram profiles and RQI valuesat different time points between natural RNase and heat-mediateddegradations according to an embodiment of the present invention. RNAextracted from rat livers incubated at room temperature prior toextraction (left panels) are compared to profiles from heat-degradedRNAs (right panels). 18S and 28S rRNA peaks map at 40 sec and 47 secrespectively. RQI value and incubation time is indicated for each graph.

One of the main differences resides in the size distribution of thedegradation products. While heat degradation produces a homogenouspopulation of fragments across all sizes, degradation by RNases yieldsfragments of discrete sizes that appear as distinct peaks or spikes inthe electropherogram. RQI calculations are not affected by the presenceof the discrete bands of degraded RNAs in the pre-18S region of theelectropherogram. The RQI software will return a valid number assumingthat both the 18S and 28S rRNA peaks have been correctly identified.FIG. 11 shows that similar RQI values, compared to heatdegraded samples,were calculated across a wide range of “natural” degradation times(0-120 min).

V. Raw Accuracy

In a study of over 2,500 RNA samples, less than 1% of the lanes (22 outof 2,500) returned anomalous RQI results (>1 RQI unit different fromvalue expected from visual inspection). Of that small percentage, themost frequent miscalled RQI value occurred due to miscalled ladderlanes, where RNA ladder fragments were misidentified by the softwareresulting in misidentification of the 18S and 28S regions. Sinceembodiments of the RQI calculation rely on these regions, their improperidentification can lead to erroneous RQI values. This problem can beeasily detected by visual inspection of the electropherogram and fixedby adjusting the peak identification parameters or by using manualintegration (for the ladder well only) to add or delete ladder peaks tocorrect the miscalled band. Contamination with DNA may also affect theRQI readings. In rare cases, the peak of contaminating DNA may beidentified as the 18S rRNA peak leading to an erroneous RQI value. Thistoo can be corrected by redefining manually where the appropriatefragment starts and ends.

VI. Confirmation with qPCR

Real-time qPCR was performed on liver carcinoma RNA samples that weredegraded for different lengths of time by incubation at 90° C. Mean CTvalues of five transcripts obtained from triplicate reactions weredetermined at a threshold of 100 relative fluorescence units (RFU) usingthe iCycler IQ real-time PCR detection system with version 3.1 software.ΔCT indicates the change in CT value over the 7 hr degradation period.Traces for the qPCR reactions from which these data were derived areshown in FIG. 12.

RNA (500 ng) was converted to cDNA using the iScripiM cDNA synthesiskit. The cDNA (10 ng) was then amplified in triplicate reactions withiQ® SYBR® Green supermix, and 0.5 uM of each primer pair for 18S rRNA,and the B-actin, GAPDH, HPRT, or B-tubulin genes using the iCycler iQ®real-time PCR detection system with version 3.1 software (Gingrich etal. 2006).

To determine the amount of RNA degradation in samples at different timepoints, qPCR was performed on the RNA samples. In these experiments,primers specific for the 18S rRNA and four selected protein-encodinggenes were used in real-time qPCR reactions to quantitate the relativeabundance of their respective transcripts at the various time points.

FIG. 12 shows plots illustrating an assessment of RNA degradation byreal-time qPCR according to an embodiment of the present invention. qPCRtraces obtained from liver carcinoma total RNA samples degraded fordifferent lengths of time and amplified using primers for the genesindicated. As one moves to the right, the different curves are for nodegradation; 1 hr degradation; 3 hr degradation; 5 hr degradation; and 7hr degradation. Mean CT values obtained from these traces are shown inTable 3 of FIG. 9C.

The results presented in FIG. 12 show that while 18S rRNA appears tohave remained mostly intact over the degradation time course, theabundance of the transcripts of the four protein-encoding genesdecreased over time.

Degradation rates for the protein-encoding gene transcripts arereflected in the increasing threshold cycle (CT). In real-time qPCRexperiments, the CT number is the number of cycles needed for amplifiedcDNA fluorescence to pass a set threshold. The CT number is used tocompare the difference in quantity of starting transcript. A differenceof one cycle reflects a 2-fold difference in the amount of startingtranscript (assuming 100% amplification efficiency).

The CT values of the qPCR reactions from the five gene transcripts areshown in Table 3 of FIG. 9C. The data indicate that the transcripts ofthe four protein-encoding genes tested were present in different amountsin the initial sample with the B-actin transcript being the mostabundant and HPRT transcript the least abundant. As expected,transcripts of the 188 rRNA were much more abundant than any of theprotein coding gene transcripts. Through the 7 hr degradation time, the18S rRNA was degraded to a much lesser extent than the protein genetranscripts, as seen by a ΔCT of 1.3, representing a 2.5-fold (21.3)decrease in transcript amount compared to the protein gene transcriptswith a ΔCT of 6.8 to 9.9, representing a 128 to 1, ODD-fold (26.8 to29.9) decrease in transcript abundance.

In order to correlate the relative amount of remaining RNA of the fivedifferent gene transcripts with the measured RQI of the RNA samples,values were plotted as shown in FIG. 13. An arbitrary value of 1 wasassigned to the transcript levels corresponding to an RQI of 10. Allother values were calculated from the CT values shown in Table 3,assuming that the number of transcripts is reduced by a factor of 2 foreach CT increase of 1.

The plot of FIG. 13 shows that the transcript levels for all five genesdecrease logarithmically relative to the RQI measurements down to an RQIvalue of 3. Below this value, the transcripts decrease at a much fasterrate. As mentioned previously, the 18S rRNA transcripts were moreabundant and less affected by degradation. The rates of decrease of thefour protein-encoding transcripts relative to their RQI measurementswere quite similar. Transcripts for HPRT and GAPDH disappeared slightlyfaster than those for B-actin and B-tubulin. For example, thetranscripts for HPRT decreased 10-fold over an RQI range of 4 units,while the transcripts for B-tubulin decreased 10-fold over an RQI rangeof 7 units.

These results demonstrate that RQI measurements can be used to estimatethe degree of degradation in an RNA sample. Although we looked at onlyfour protein-encoding genes, they all appeared to degrade to differentextents relative to the RQI score. This indicates that one mayre-evaluate RNA degradation states when comparing or performing qPCR toensure reliable results. For example, the color coding may change or theRQI values may change depending on what specific biomolecule of interestis being used (e.g. amplified). Regardless though, the RQI stillprovides a consistent value for a particular degradation state. It is upto the researcher of a specific technique to identify which RQI valuesare required for a specific experiment.

Therefore, embodiments have been shown to determine a level of integrity(e.g. the RQI value) with an efficient method that takes into accountonly three regions of the electropherogram and that has been shown to beaccurate.

What is claimed is:
 1. A method of improving accuracy andreproducibility of determining a level of integrity of a sample ofribonucleic acid (RNA) and/or deoxyribonucleic acid (DNA) molecules, themethod comprising: receiving a first size profile of the sample of theRNA and/or DNA molecules, wherein a size profile provides a measure of adistribution of values of at least one dimension of the RNA and/or DNAmolecules, in the sample, the at least one dimension including lengthand/or weight; comparing, with an electrophoresis system, the first sizeprofile to a plurality of reference size profiles, wherein eachreference size profile correlates to a different level of integrity; andbased on a similarity of the first size profile to one or more of thereference size profiles, determining, with the electrophoresis system,the level of integrity of the sample of RNA and/or DNA molecules,wherein the plurality of reference size profiles is obtained by: at eachof a plurality of different elapsed times relative to an initial time:measuring a respective reference size profile of a reference sample ofRNA and/or DNA molecules selected from a group of reference sampleshaving about the same initial integrity, wherein each respectivereference size profile corresponds to a different amount of degradationof the reference sample, wherein each reference size profile provides ameasure of a distribution of values of the at least one dimension of theRNA and/or DNA molecules in the reference sample; and mapping eachreference size profile to a level of integrity, a highest integritylevel of reference size profile being measured at the initial time, andeach successive lower integrity level of reference size profile beingmeasured at a longer elapsed time from the initial time.
 2. The methodof claim 1, wherein the reference size profiles are derived from one ormore reference samples containing RNA and/or DNA molecules of the sameorigin and the same concentration.
 3. The method of claim 1, wherein thelevel of integrity is expressed as a numerical value withinpredetermined scale.
 4. The method of claim 1, wherein the differentelapsed times of degradation of the reference size profiles are zero andsuccessive periodic times.
 5. The method of claim 1, wherein thereference size profiles map linearly to different levels of integrity.6. The method of claim 1, wherein a size profile comprises a pluralityof ratios of at least three regions, wherein each region corresponds toa different amount of time for RNA and/or DNA molecules of the sample toreach a detection point, wherein RNA and/or DNA molecules of differentsize reach the detection point at different times.
 7. The method ofclaim 6, wherein the comparing includes: comparing one or more sizefeatures of the first size profile to corresponding size features of thereference size profiles, wherein determining the level of integrity ofthe sample of RNA and/or DNA molecules includes: based on the comparing,determining an integrity value for each size feature of the first sizeprofile; and averaging the integrity values to determine the level ofintegrity of the sample of RNA and/or DNA molecules.
 8. The method ofclaim 7, wherein the one or more size features include a ratio of areasof a size profile around the rRNA peaks of 18S and 28S.
 9. The method ofclaim 7, wherein averaging weights one size feature higher if theintegrity value of the one size feature is higher than a thresholdvalue.
 10. The method of claim 7, wherein for each size feature of thefirst size profile: comparing one or more size features of the firstsize profile to corresponding size features of the reference sizeprofiles includes: identifying two reference profiles havingcorresponding size features with values between which lies the value forthe respective size feature of the first size profile; and calculatingthe differences between the respective size feature of the first sizeprofile and the values of the corresponding size features of the tworeference profiles, and determining an integrity value includes:interpolating between the values of the corresponding size features ofthe two reference size profiles to determine the integrity value of therespective size feature.
 11. The method of claim 1, wherein the sizeprofile is an electropherogram.
 12. A computer program productcomprising a non-transitory computer readable medium storing a pluralityof instructions for controlling a processor to perform an operation forof determining a level of integrity of a sample of ribonucleic acid(RNA) and/or deoxyribonucleic acid (DNA) molecules, the instructionscomprising: receiving a first size profile of the sample of the RNAand/or DNA molecules, wherein a size profile provides a measure of adistribution of values of at least one dimension of the RNA and/or DNAmolecules in the sample, the at least one dimension including lengthand/or weight; comparing the first size profile to a plurality ofreference size profiles, wherein each reference size profile correlatesto a different level of integrity; and based on a similarity of thefirst size profile to one or more of the reference size profiles,determining the level of integrity of the sample of RNA and/or DNAmolecules, wherein the plurality of reference size profiles is obtainedby: at each of a plurality of different elapsed times relative to aninitial time: measuring a respective reference size profile of areference sample of RNA and/or DNA molecules selected from a group ofreference samples having about the same initial integrity, wherein eachrespective reference size profile corresponds to a different amount ofdegradation of the reference sample, wherein each reference size profileprovides a measure of a distribution of values of the at least onedimension of the RNA and/or DNA molecules in the reference sample; andmapping each reference size profile to a level of integrity, a highestintegrity level of reference size profile being measured at the initialtime, and each successive lower integrity level of reference sizeprofile being measured at a longer elapsed time from the initial time.13. An electrophoresis system comprising: a voltage source; a detector;the computer program product of claim 12; and one or more processorscommunicably coupled with the detector and the computer program product.14. The electrophoresis system of claim 13, wherein the computer programproduct stores the reference size profiles.
 15. The electrophoresissystem of claim 13, further comprising a light source that excitesluminescent markers on the biomolecules, the light source illuminating afirst electromagnetic radiation at a detection point, and wherein thedetector detects a second electromagnetic radiation emitted from theexcited biomolecules at the detection point at a specific instance intime.
 16. A method of deriving reference size profiles for anelectrophoresis system, the method comprising: receiving a referencesample of biomolecules; at each of a plurality of different elapsedtimes relative to an initial time: measuring, with an electrophoresissystem, a respective size profile of the reference sample ofbiomolecules, wherein a size profile provides a measure of adistribution of values of at least one dimension of the biomolecules inthe reference sample, wherein each respective size profile correspondsto a different amount of degradation of the reference sample; andmapping each size profile to a level of integrity, wherein a sizeprofile measured at a later elapsed time maps to a lower level ofintegrity.
 17. The method of claim 16, further comprising: storing, in acomputer readable medium of the electrophoresis system, the sizeprofiles associated with the corresponding level of integrity.
 18. Themethod of claim 16, wherein the reference sample has no degradationprior to the measurement of a first size profile at the initial time.19. The method of claim 16, wherein the mapping is non-linear.
 20. Themethod of claim 16, further comprising: degrading the reference sampleat the plurality of elapsed times by subjecting the reference sample toheat.
 21. The method of claim 17, further comprising: repeating for oneor more additional reference samples, each selected from a group ofreference samples having about the same initial integrity; and taking anaverage of the size profiles taken at each elapsed time, wherein theaverage of the size profiles is stored in the computer readable medium.22. The method of claim 16, wherein the plurality of different elapsedtimes are predetermined, and wherein a respective size profile ismeasured when a predetermined elapsed times is reached.